{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tuning query parameters for the MSMARCO Document dataset\n",
    "\n",
    "The following shows a principled, data-driven approach to tuning parameters of a basic query, such as field boosts, using the MSMARCO Document dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import importlib\n",
    "import os\n",
    "import sys\n",
    "\n",
    "from elasticsearch import Elasticsearch\n",
    "from skopt.plots import plot_objective"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# project library\n",
    "sys.path.insert(0, os.path.abspath('..'))\n",
    "\n",
    "import qopt\n",
    "importlib.reload(qopt)\n",
    "\n",
    "from qopt.notebooks import evaluate_mrr100_dev, optimize_query_mrr100\n",
    "from qopt.optimize import Config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# use a local Elasticsearch or Cloud instance (https://cloud.elastic.co/)\n",
    "# es = Elasticsearch('http://localhost:9200')\n",
    "es = Elasticsearch('http://35.234.93.126:9200')\n",
    "\n",
    "# set the parallelization parameter `max_concurrent_searches` for the Rank Evaluation API calls\n",
    "# max_concurrent_searches = 10\n",
    "max_concurrent_searches = 30\n",
    "\n",
    "index = 'msmarco-document'\n",
    "template_id = 'cross_fields'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Baseline evaluation\n",
    "\n",
    "Let's look at a basic query that might be used to search documents that have multuple fields. This query uses [the `multi_match` query of type `cross_fields`](https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-multi-match-query.html#type-cross-fields) to search for query terms across the `url`, `title`, and `body` fields. Here's what the search template looks like that we'll be using:\n",
    "\n",
    "```json\n",
    "{\n",
    "    \"query\": {\n",
    "      \"multi_match\": {\n",
    "        \"type\": \"cross_fields\",\n",
    "        \"query\": \"{{query_string}}\",\n",
    "        \"operator\": \"{{operator}}\",\n",
    "        \"minimum_should_match\": \"{{minimum_should_match}}%\",\n",
    "        \"tie_breaker\": \"{{tie_breaker}}\",\n",
    "        \"fields\": [\n",
    "          \"url^{{url|boost}}\",\n",
    "          \"title^{{title|boost}}\",\n",
    "          \"body^{{body|boost}}\"\n",
    "        ]\n",
    "      }\n",
    "    }\n",
    "}\n",
    "```\n",
    "\n",
    "First we'll run an evaluation on the \"development\" (or `dev` in MSMARCO terms) dataset using the standardized metric for MSMARCO, MRR@100. This will show us what our baseline is that we want to improve against. We'll use default values for all parameters in the template above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Evaluation with: MRR@100\n",
      "Score: 0.2683\n",
      "CPU times: user 1.87 s, sys: 621 ms, total: 2.49 s\n",
      "Wall time: 3min 48s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "_ = evaluate_mrr100_dev(es, max_concurrent_searches, index, template_id,\n",
    "    params={\n",
    "        'operator': 'OR',\n",
    "        'minimum_should_match': 50,  # in percent/%\n",
    "        'tie_breaker': 0.0,\n",
    "        'url|boost': 1.0,\n",
    "        'title|boost': 1.0,\n",
    "        'body|boost': 1.0,\n",
    "    })"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we have a baseline score that we'll iterate towards improving."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Getting started with tuning: low dimensionality and discrete parameter values\n",
    "\n",
    "There's a lot of parameters that we need to choose for this query. There's three boost parameters (one for each field) and then the `operator`, `minimum_should_match`, and `tie_breaker` parameters. We're going to break this up into steps and optimize using basic approaches first. Breaking things up like this allows us to tackle the problem in steps and avoids introducing a large amount of complexity and what is called a large parameter space. A parameter space is the total scope of all parameters combined, and all possible values of those parameters. If we have 3 parameters, we have a 3 _dimensional_ space and each possible combination of parameters is what makes up the coordinates of that space.\n",
    "\n",
    "Let's start with just using all the default values but looking at the difference between the `operator` values `['OR', 'AND']` in combination with a few optoins for `minimum_should_match`, since these parameters sometimes have an effect together. Since we have just two dimensions and a few possible values each, the parameter space is very small. In this case it's `operator:2 * minimum_should_match:5 = 10`. That's pretty small and so we'll use a simple grid search that will test every possible combination of those parmeters, 10 tests in all.\n",
    "\n",
    "When we do this search over the parameters space, we'll use a different dataset to avoid overfitting (coming up with parameter values that work only on one dataset) and then do another evaluation on the dev dataset (as above) after finding what we think are the optimal parameter values in order to check our results. To make this process a bit faster (although less robust), we'll continue to use MRR@100 but with a training query dataset of just 1,000 queries compared to the over 3,000 in the development dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimizing parameters\n",
      " - metric: MRR@100\n",
      " - queries: data/msmarco-document-sampled-queries.1000.tsv\n",
      " - queries: data/msmarco/document/msmarco-doctrain-qrels.tsv\n",
      " - iteration 1 scored 0.2282 with: {'operator': 'OR', 'minimum_should_match': 30}\n",
      " - iteration 2 scored 0.1999 with: {'operator': 'AND', 'minimum_should_match': 30}\n",
      " - iteration 3 scored 0.2282 with: {'operator': 'OR', 'minimum_should_match': 40}\n",
      " - iteration 4 scored 0.1999 with: {'operator': 'AND', 'minimum_should_match': 40}\n",
      " - iteration 5 scored 0.2280 with: {'operator': 'OR', 'minimum_should_match': 50}\n",
      " - iteration 6 scored 0.1999 with: {'operator': 'AND', 'minimum_should_match': 50}\n",
      " - iteration 7 scored 0.2279 with: {'operator': 'OR', 'minimum_should_match': 60}\n",
      " - iteration 8 scored 0.1999 with: {'operator': 'AND', 'minimum_should_match': 60}\n",
      " - iteration 9 scored 0.2280 with: {'operator': 'OR', 'minimum_should_match': 70}\n",
      " - iteration 10 scored 0.1999 with: {'operator': 'AND', 'minimum_should_match': 70}\n",
      "Best score: 0.2282\n",
      "Best params: {'operator': 'OR', 'minimum_should_match': 30}\n",
      "Final params: {'tie_breaker': 0.0, 'url|boost': 1.0, 'title|boost': 1.0, 'body|boost': 1.0, 'operator': 'OR', 'minimum_should_match': 30}\n",
      "\n",
      "CPU times: user 5.27 s, sys: 1.87 s, total: 7.14 s\n",
      "Wall time: 2min 22s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "_ = optimize_query_mrr100(es, max_concurrent_searches, index, template_id,\n",
    "    config_space=Config.parse({\n",
    "        'method': 'grid',\n",
    "        'space': {\n",
    "            'operator': ['OR', 'AND'],\n",
    "            'minimum_should_match': [30, 40, 50, 60, 70],\n",
    "        },\n",
    "        'default': {\n",
    "            'tie_breaker': 0.0,\n",
    "            'url|boost': 1.0,\n",
    "            'title|boost': 1.0,\n",
    "            'body|boost': 1.0,\n",
    "        }\n",
    "    }))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The first thing we notice is that there's really not much difference between the variants of `minimum_should_match`. There is however a very big difference between `OR` and `AND` `operator`. It's pretty clear that with the kinds of queries we get in this dataset (long-form, natural language questions), that `OR` is always better than `AND`. Based on this we're going to just assume that `OR` is always the better option and we'll continue to look for a good `minimum_should_match`. Let's do that in combination with `tie_breaker` now since those two parameters can have an impact on each other. We'll start simple again with a grid search over a limited number of parameter values for each, all of which are discrete values. With two dimensions and five parameter values each, we have a parameter space of size 25 and can test every possible value in a reasonable amount of time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimizing parameters\n",
      " - metric: MRR@100\n",
      " - queries: data/msmarco-document-sampled-queries.1000.tsv\n",
      " - queries: data/msmarco/document/msmarco-doctrain-qrels.tsv\n",
      " - iteration 1 scored 0.2282 with: {'minimum_should_match': 30, 'tie_breaker': 0.0}\n",
      " - iteration 2 scored 0.2514 with: {'minimum_should_match': 30, 'tie_breaker': 0.25}\n",
      " - iteration 3 scored 0.2425 with: {'minimum_should_match': 30, 'tie_breaker': 0.5}\n",
      " - iteration 4 scored 0.2286 with: {'minimum_should_match': 30, 'tie_breaker': 0.75}\n",
      " - iteration 5 scored 0.2178 with: {'minimum_should_match': 30, 'tie_breaker': 1.0}\n",
      " - iteration 6 scored 0.2282 with: {'minimum_should_match': 40, 'tie_breaker': 0.0}\n",
      " - iteration 7 scored 0.2532 with: {'minimum_should_match': 40, 'tie_breaker': 0.25}\n",
      " - iteration 8 scored 0.2436 with: {'minimum_should_match': 40, 'tie_breaker': 0.5}\n",
      " - iteration 9 scored 0.2292 with: {'minimum_should_match': 40, 'tie_breaker': 0.75}\n",
      " - iteration 10 scored 0.2184 with: {'minimum_should_match': 40, 'tie_breaker': 1.0}\n",
      " - iteration 11 scored 0.2280 with: {'minimum_should_match': 50, 'tie_breaker': 0.0}\n",
      " - iteration 12 scored 0.2542 with: {'minimum_should_match': 50, 'tie_breaker': 0.25}\n",
      " - iteration 13 scored 0.2446 with: {'minimum_should_match': 50, 'tie_breaker': 0.5}\n",
      " - iteration 14 scored 0.2306 with: {'minimum_should_match': 50, 'tie_breaker': 0.75}\n",
      " - iteration 15 scored 0.2179 with: {'minimum_should_match': 50, 'tie_breaker': 1.0}\n",
      " - iteration 16 scored 0.2279 with: {'minimum_should_match': 60, 'tie_breaker': 0.0}\n",
      " - iteration 17 scored 0.2537 with: {'minimum_should_match': 60, 'tie_breaker': 0.25}\n",
      " - iteration 18 scored 0.2451 with: {'minimum_should_match': 60, 'tie_breaker': 0.5}\n",
      " - iteration 19 scored 0.2309 with: {'minimum_should_match': 60, 'tie_breaker': 0.75}\n",
      " - iteration 20 scored 0.2193 with: {'minimum_should_match': 60, 'tie_breaker': 1.0}\n",
      " - iteration 21 scored 0.2280 with: {'minimum_should_match': 70, 'tie_breaker': 0.0}\n",
      " - iteration 22 scored 0.2521 with: {'minimum_should_match': 70, 'tie_breaker': 0.25}\n",
      " - iteration 23 scored 0.2433 with: {'minimum_should_match': 70, 'tie_breaker': 0.5}\n",
      " - iteration 24 scored 0.2284 with: {'minimum_should_match': 70, 'tie_breaker': 0.75}\n",
      " - iteration 25 scored 0.2188 with: {'minimum_should_match': 70, 'tie_breaker': 1.0}\n",
      "Best score: 0.2542\n",
      "Best params: {'minimum_should_match': 50, 'tie_breaker': 0.25}\n",
      "Final params: {'operator': 'OR', 'url|boost': 1.0, 'title|boost': 1.0, 'body|boost': 1.0, 'minimum_should_match': 50, 'tie_breaker': 0.25}\n",
      "\n",
      "CPU times: user 11.1 s, sys: 3.88 s, total: 15 s\n",
      "Wall time: 9min 16s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "_, _, final_params_msmtb, _ = optimize_query_mrr100(es, max_concurrent_searches, index, template_id,\n",
    "    config_space=Config.parse({\n",
    "        'method': 'grid',\n",
    "        'space': {\n",
    "            'minimum_should_match': [30, 40, 50, 60, 70],\n",
    "            'tie_breaker': [0.0, 0.25, 0.5, 0.75, 1.0],\n",
    "        },\n",
    "        'default': {\n",
    "            'operator': 'OR',\n",
    "            'url|boost': 1.0,\n",
    "            'title|boost': 1.0,\n",
    "            'body|boost': 1.0,\n",
    "        }\n",
    "    }))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Well that looks pretty good and we see some improvements on the training set. Let's evaluate on the development dataset now using the best parameters we've found so far. This will show us where we are relative to the baseline query."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Evaluation with: MRR@100\n",
      "Score: 0.2841\n",
      "CPU times: user 1.78 s, sys: 568 ms, total: 2.35 s\n",
      "Wall time: 1min 36s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "_ = evaluate_mrr100_dev(es, max_concurrent_searches, index, template_id, params=final_params_msmtb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Definitely a good improvement and all we've done is optimize a few basic query parameters!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Advanced tuning: high dimensionality and continuous parameter values\n",
    "\n",
    "So the question now is, can we improve this query further by tuning each of the field boosts? One of the difficulties with picking field boosts intuitively is that they are not necesarrily interpretable in relation to each other. That is, a weight of `2.0` on the `title` field does not mean that it is two times more important than the `body` field with a boost of `1.0`. In order to find the best field boosts, we'll need to search over a parameter space that includes a continuous range from `0.0` to `10.0`.\n",
    "\n",
    "We can't just use a grid search as we did above, testing each possible combination of the three field boosts, as an exhaustive search would require 1,000 evaluations if we test just at steps of `1` and no finer (10 steps per parameter, 3 parameters, makes `10 * 10 * 10` evaluations). Since the evaluation method is time consuming and a grid search over all combinations would be prohibitive, we'll use [Bayesian optimization](https://towardsdatascience.com/a-conceptual-explanation-of-bayesian-model-based-hyperparameter-optimization-for-machine-learning-b8172278050f) to pick the combinations of boosts. We're going to use a lot of iterations and probably more than necessary, but it'll be useful in a later step to plot the parameter space. Note that there are two iteration parameters that we need to set. First the `num_iterations` which controls the total numnber of iterations in the process. Second the `num_initial_points` is used to control the number of iterations that will randomly select parameter values from the parameter space, which are used to seed the Bayesian optimization process. That means the number of iterations that actually use Bayesian optimization (prior results used to select the next parameter values to try) is in fact `num_iterations - num_initial_points`. It's important to not set the `num_initial_points` too low or your Bayesian process may find the best parameters much more slowly (i.e. need more total `num_iterations`).\n",
    "\n",
    "Since we already found the optimal `operator`, `minimum_should_match` and `tie_breaker` parameters in the steps above, we'll bring those forward as default parameters that don't need to optimized any further. The current best parameters are as follows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'operator': 'OR',\n",
       " 'url|boost': 1.0,\n",
       " 'title|boost': 1.0,\n",
       " 'body|boost': 1.0,\n",
       " 'minimum_should_match': 50,\n",
       " 'tie_breaker': 0.25}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_params_msmtb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimizing parameters\n",
      " - metric: MRR@100\n",
      " - queries: data/msmarco-document-sampled-queries.1000.tsv\n",
      " - queries: data/msmarco/document/msmarco-doctrain-qrels.tsv\n",
      " - iteration 1 scored 0.2439 with: {'url|boost': 5.088218570463118, 'title|boost': 0.12453189316449789, 'body|boost': 5.2056967250459465}\n",
      " - iteration 2 scored 0.2439 with: {'url|boost': 1.214222002655552, 'title|boost': 2.041510984015977, 'body|boost': 6.867418802099495}\n",
      " - iteration 3 scored 0.1758 with: {'url|boost': 5.135369118260416, 'title|boost': 6.046469099544289, 'body|boost': 0.6984090293583113}\n",
      " - iteration 4 scored 0.2576 with: {'url|boost': 1.5442807512197678, 'title|boost': 8.699722886772154, 'body|boost': 4.20477072941809}\n",
      " - iteration 5 scored 0.1801 with: {'url|boost': 8.882958864277958, 'title|boost': 3.187169476321448, 'body|boost': 4.190231080345567}\n",
      " - iteration 6 scored 0.2393 with: {'url|boost': 3.3235083860000443, 'title|boost': 5.577529520848545, 'body|boost': 2.4180517612547976}\n",
      " - iteration 7 scored 0.1762 with: {'url|boost': 2.044185039760142, 'title|boost': 2.100418204768428, 'body|boost': 0.5551889603239092}\n",
      " - iteration 8 scored 0.2496 with: {'url|boost': 0.7714320324038094, 'title|boost': 4.929167602731011, 'body|boost': 9.696047808966672}\n",
      " - iteration 9 scored 0.2564 with: {'url|boost': 1.7500532307200047, 'title|boost': 4.00326744974457, 'body|boost': 5.82920580182714}\n",
      " - iteration 10 scored 0.1596 with: {'url|boost': 8.949408391609406, 'title|boost': 2.453713567282039, 'body|boost': 1.4812524424521458}\n",
      " - iteration 11 scored 0.2500 with: {'url|boost': 4.615183237945444, 'title|boost': 2.353328017262812, 'body|boost': 5.805077387610557}\n",
      " - iteration 12 scored 0.1649 with: {'url|boost': 9.415594569744108, 'title|boost': 4.18084685807385, 'body|boost': 2.6898832307241354}\n",
      " - iteration 13 scored 0.2396 with: {'url|boost': 2.9944816769180655, 'title|boost': 0.6379307700776516, 'body|boost': 9.895748323855644}\n",
      " - iteration 14 scored 0.1936 with: {'url|boost': 4.710659749915392, 'title|boost': 4.712891030963389, 'body|boost': 2.246125562928774}\n",
      " - iteration 15 scored 0.2571 with: {'url|boost': 3.980906567042146, 'title|boost': 4.839805796693688, 'body|boost': 5.301741185769555}\n",
      " - iteration 16 scored 0.1762 with: {'url|boost': 7.323948746511084, 'title|boost': 7.67475735226267, 'body|boost': 1.8963893142811332}\n",
      " - iteration 17 scored 0.1650 with: {'url|boost': 5.365181964981942, 'title|boost': 2.2774932640346406, 'body|boost': 1.5769182847090537}\n",
      " - iteration 18 scored 0.2666 with: {'url|boost': 1.5347798498597356, 'title|boost': 9.77089639137353, 'body|boost': 7.442085609500625}\n",
      " - iteration 19 scored 0.1575 with: {'url|boost': 9.070640571956968, 'title|boost': 4.45025448939939, 'body|boost': 0.28245581587606267}\n",
      " - iteration 20 scored 0.2145 with: {'url|boost': 6.615061445621256, 'title|boost': 6.174563121441324, 'body|boost': 4.2276022874139905}\n",
      " - iteration 21 scored 0.1620 with: {'url|boost': 2.7012512953366015, 'title|boost': 0.5662862847192619, 'body|boost': 0.5344303576960797}\n",
      " - iteration 22 scored 0.2563 with: {'url|boost': 0.5391042509235856, 'title|boost': 8.973267516682546, 'body|boost': 4.507013928921801}\n",
      " - iteration 23 scored 0.1904 with: {'url|boost': 4.918802296302357, 'title|boost': 8.516206207590814, 'body|boost': 0.19106525136031507}\n",
      " - iteration 24 scored 0.2164 with: {'url|boost': 8.229276325174878, 'title|boost': 8.531931289495905, 'body|boost': 5.195230366845819}\n",
      " - iteration 25 scored 0.2430 with: {'url|boost': 3.0062694161907118, 'title|boost': 8.501293261856622, 'body|boost': 3.2091875452182923}\n",
      " - iteration 26 scored 0.2581 with: {'url|boost': 5.497211913316614, 'title|boost': 10.0, 'body|boost': 10.0}\n",
      " - iteration 27 scored 0.2620 with: {'url|boost': 3.656152021943995, 'title|boost': 10.0, 'body|boost': 7.500233255112616}\n",
      " - iteration 28 scored 0.2583 with: {'url|boost': 0.0, 'title|boost': 10.0, 'body|boost': 10.0}\n",
      " - iteration 29 scored 0.2542 with: {'url|boost': 10.0, 'title|boost': 10.0, 'body|boost': 10.0}\n",
      " - iteration 30 scored 0.2432 with: {'url|boost': 10.0, 'title|boost': 0.0, 'body|boost': 10.0}\n",
      " - iteration 31 scored 0.2675 with: {'url|boost': 0.0, 'title|boost': 10.0, 'body|boost': 7.097102887853742}\n",
      " - iteration 32 scored 0.2698 with: {'url|boost': 2.296376877860631, 'title|boost': 10.0, 'body|boost': 6.0332229396521235}\n",
      " - iteration 33 scored 0.2508 with: {'url|boost': 6.647481188950108, 'title|boost': 5.358457003998134, 'body|boost': 8.59408737517023}\n",
      " - iteration 34 scored 0.2691 with: {'url|boost': 2.367654890045655, 'title|boost': 10.0, 'body|boost': 6.022093297052122}\n",
      " - iteration 35 scored 0.2644 with: {'url|boost': 2.2818799037559585, 'title|boost': 7.574174994815637, 'body|boost': 6.185924778162914}\n",
      " - iteration 36 scored 0.2354 with: {'url|boost': 0.0, 'title|boost': 10.0, 'body|boost': 2.0537845123722316}\n",
      " - iteration 37 scored 0.2667 with: {'url|boost': 0.0, 'title|boost': 10.0, 'body|boost': 6.537081898852963}\n",
      " - iteration 38 scored 0.2616 with: {'url|boost': 2.643848233578951, 'title|boost': 10.0, 'body|boost': 10.0}\n",
      " - iteration 39 scored 0.2705 with: {'url|boost': 1.0129720302556104, 'title|boost': 5.818478716515356, 'body|boost': 3.736613263685484}\n",
      " - iteration 40 scored 0.2475 with: {'url|boost': 10.0, 'title|boost': 5.932699984384042, 'body|boost': 10.0}\n",
      " - iteration 41 scored 0.2516 with: {'url|boost': 0.0, 'title|boost': 2.7168887049111095, 'body|boost': 3.963751301532432}\n",
      " - iteration 42 scored 0.2562 with: {'url|boost': 4.115704829670892, 'title|boost': 6.478885432070581, 'body|boost': 10.0}\n",
      " - iteration 43 scored 0.2628 with: {'url|boost': 2.027851260921649, 'title|boost': 5.718268064451686, 'body|boost': 4.217871904673669}\n",
      " - iteration 44 scored 0.2454 with: {'url|boost': 6.820628170354972, 'title|boost': 0.20242520842343453, 'body|boost': 7.838400793355449}\n",
      " - iteration 45 scored 0.2634 with: {'url|boost': 0.0, 'title|boost': 6.786775337347516, 'body|boost': 5.761864987809019}\n",
      " - iteration 46 scored 0.2568 with: {'url|boost': 7.6090790259196615, 'title|boost': 10.0, 'body|boost': 8.248143766935435}\n",
      " - iteration 47 scored 0.2637 with: {'url|boost': 0.0, 'title|boost': 10.0, 'body|boost': 8.347851100247212}\n",
      " - iteration 48 scored 0.2680 with: {'url|boost': 1.4988362368469332, 'title|boost': 10.0, 'body|boost': 6.65949463901717}\n",
      " - iteration 49 scored 0.2689 with: {'url|boost': 0.0, 'title|boost': 5.942599629030903, 'body|boost': 3.8329060733604274}\n",
      " - iteration 50 scored 0.2478 with: {'url|boost': 0.0, 'title|boost': 5.901354883784751, 'body|boost': 2.644770347884716}\n",
      "Best score: 0.2705\n",
      "Best params: {'url|boost': 1.0129720302556104, 'title|boost': 5.818478716515356, 'body|boost': 3.736613263685484}\n",
      "Final params: {'operator': 'OR', 'url|boost': 1.0129720302556104, 'title|boost': 5.818478716515356, 'body|boost': 3.736613263685484, 'minimum_should_match': 50, 'tie_breaker': 0.25}\n",
      "\n",
      "CPU times: user 1min 5s, sys: 16.9 s, total: 1min 22s\n",
      "Wall time: 20min 2s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "_, _, final_params_boosts, metadata_boosts = optimize_query_mrr100(es, max_concurrent_searches, index, template_id,\n",
    "    config_space=Config.parse({\n",
    "        'method': 'bayesian',\n",
    "        'num_iterations': 50,\n",
    "        'num_initial_points': 25,\n",
    "        'space': {\n",
    "            'url|boost': { 'low': 0.0, 'high': 10.0 },\n",
    "            'title|boost': { 'low': 0.0, 'high': 10.0 },\n",
    "            'body|boost': { 'low': 0.0, 'high': 10.0 },\n",
    "        },\n",
    "        'default': final_params_msmtb,\n",
    "    }))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Evaluation with: MRR@100\n",
      "Score: 0.3007\n",
      "CPU times: user 1.93 s, sys: 760 ms, total: 2.69 s\n",
      "Wall time: 1min 40s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "_ = evaluate_mrr100_dev(es, max_concurrent_searches, index, template_id, params=final_params_boosts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Great! It looks like we made an improvement over both the baseline and the preivous best parameters found. This example shows how important it is to not tune field boosts manually, as there is no intuitive relationship between the boost values of fields.\n",
    "\n",
    "Note that due to some randomness in executions of this process, re-running the optimization process may provide slightly different optimal boosts. Most importantly for field boost tuning in general, the relative value between the fields should be about the same."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exploring a parameter space\n",
    "\n",
    "Now that we see the results of a parameter tuning process we can actually look at the details to understand a little bit about the field boost parameter space in particlar. That is, for every combination of the three boost parameters that we tried, we can get a 3-dimensional space and look at what kind of relationships there are between the various dimensions in the parameter space. Here's a plot showing the three parameters and all the combinations that were attempted. Note that we invert the MRR score (multiple by `-1`) since the library we are relying ([scikit-optimize](https://scikit-optimize.github.io/)) on wants to *minimize* a score, while MRR should be *maximized*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = plot_objective(metadata_boosts, sample_source='result')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Experiment: all-in-one tuning\n",
    "\n",
    "You might be wondering why bother doing the tuning step-wise, first searching through a few parameters, then moving onto the next set. When parameters are dependent on others, it might make sense to put all the parameters into a single, giant parameters space and try and optimize all at once. This is a more difficult optimization problem as the space is huge, but let's give it a shot and see what happens."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Same number of iterations, same parameter space\n",
    "\n",
    "First we'll use the same number of total) iterations and combined parameter space as in the above steps. This is more of an apples-to-apples comparison then. However since we can easily search over continuous parameter spaces using Bayesian optimization techniques, we'll make it slightly harder but more complete by allowing for any value in our range of `minimum_should_match` and `tie_breaker`, instead of providing just the limited, discrete values as we did above (that was more for a grid search example than anything else).\n",
    "\n",
    "Note that in the following examples we supress progress output since we are using so many iterations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimizing parameters\n",
      " - metric: MRR@100\n",
      " - queries: data/msmarco-document-sampled-queries.1000.tsv\n",
      " - queries: data/msmarco/document/msmarco-doctrain-qrels.tsv\n",
      "Best score: 0.2688\n",
      "Best params: {'minimum_should_match': 52, 'tie_breaker': 1.0, 'url|boost': 0.0, 'title|boost': 10.0, 'body|boost': 10.0}\n",
      "Final params: {'operator': 'OR', 'minimum_should_match': 52, 'tie_breaker': 1.0, 'url|boost': 0.0, 'title|boost': 10.0, 'body|boost': 10.0}\n",
      "\n",
      "CPU times: user 2min 7s, sys: 24.6 s, total: 2min 31s\n",
      "Wall time: 33min 12s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "_, _, final_params_boosts, metadata_boosts = optimize_query_mrr100(es, max_concurrent_searches, index, template_id,\n",
    "    config_space=Config.parse({\n",
    "        'method': 'bayesian',\n",
    "        'num_iterations': 75,\n",
    "        'num_initial_points': 30,\n",
    "        'space': {\n",
    "            'minimum_should_match': { 'low': 30, 'high': 70 },\n",
    "            'tie_breaker': { 'low': 0.0, 'high': 1.0 },\n",
    "            'url|boost': { 'low': 0.0, 'high': 10.0 },\n",
    "            'title|boost': { 'low': 0.0, 'high': 10.0 },\n",
    "            'body|boost': { 'low': 0.0, 'high': 10.0 },\n",
    "        },\n",
    "        'default': {\n",
    "            'operator': 'OR',\n",
    "        }\n",
    "    }),\n",
    "    verbose=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 25 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = plot_objective(metadata_boosts, sample_source='result')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Evaluation with: MRR@100\n",
      "Score: 0.2945\n",
      "CPU times: user 1.98 s, sys: 684 ms, total: 2.66 s\n",
      "Wall time: 1min 27s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "_ = evaluate_mrr100_dev(es, max_concurrent_searches, index, template_id, params=final_params_boosts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ok, so not a big difference to the step-wise method we used above, but maybe it was a bit simpler to just throw in a huge parameter space."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### More iterations, smaller parameter space using hints from prior grid search\n",
    "\n",
    "Let's see if we can do even better by throwing more iterations into it, and by using a smaller search space for parameters that we already have a good range for `minimum_should_match` and `tie_breaker`, from the above grid search. This is kind of a hint and maybe not a fair comparison, but let's see if it makes any difference. We're not against using any prior knowledge to our advantage!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimizing parameters\n",
      " - metric: MRR@100\n",
      " - queries: data/msmarco-document-sampled-queries.1000.tsv\n",
      " - queries: data/msmarco/document/msmarco-doctrain-qrels.tsv\n",
      "Best score: 0.2723\n",
      "Best params: {'minimum_should_match': 40, 'tie_breaker': 0.2986382618036153, 'url|boost': 0.8137279950560328, 'title|boost': 10.0, 'body|boost': 7.785349592704518}\n",
      "Final params: {'operator': 'OR', 'minimum_should_match': 40, 'tie_breaker': 0.2986382618036153, 'url|boost': 0.8137279950560328, 'title|boost': 10.0, 'body|boost': 7.785349592704518}\n",
      "\n",
      "CPU times: user 3min 7s, sys: 33.9 s, total: 3min 41s\n",
      "Wall time: 46min 45s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "_, _, final_params_boosts, metadata_boosts = optimize_query_mrr100(es, max_concurrent_searches, index, template_id,\n",
    "    config_space=Config.parse({\n",
    "        'method': 'bayesian',\n",
    "        'num_iterations': 100,\n",
    "        'num_initial_points': 40,\n",
    "        'space': {\n",
    "            'minimum_should_match': { 'low': 40, 'high': 60 },  # 50 +/- 10\n",
    "            'tie_breaker': { 'low': 0.1, 'high': 0.4 },  # 0.25 +/- 0.15\n",
    "            'url|boost': { 'low': 0.0, 'high': 10.0 },\n",
    "            'title|boost': { 'low': 0.0, 'high': 10.0 },\n",
    "            'body|boost': { 'low': 0.0, 'high': 10.0 },\n",
    "        },\n",
    "        'default': {\n",
    "            'operator': 'OR',\n",
    "        }\n",
    "    }),\n",
    "    verbose=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 25 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = plot_objective(metadata_boosts, sample_source='result')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Evaluation with: MRR@100\n",
      "Score: 0.2993\n",
      "CPU times: user 1.96 s, sys: 598 ms, total: 2.56 s\n",
      "Wall time: 2min 4s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "_ = evaluate_mrr100_dev(es, max_concurrent_searches, index, template_id, params=final_params_boosts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looks like we did about the same as the other methods in terms of MRR@100. In terms of simplicity though, this approach definitely wins as we can throw all the parameters in at once and not have to think too much about order and parameter dependencies."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Random search\n",
    "\n",
    "Something we haven't tried yet is a fully random search. When initializing Bayesian optimization, we're doing a uniform random sample from the parameter space, then using those points to seed the process. A common approach is actually to just do all your search iterations with random parameters. Let's use the same parameter space and try out a fully random search with a lot of iterations and see what happens."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimizing parameters\n",
      " - metric: MRR@100\n",
      " - queries: data/msmarco-document-sampled-queries.1000.tsv\n",
      " - queries: data/msmarco/document/msmarco-doctrain-qrels.tsv\n",
      "Best score: 0.2693\n",
      "Best params: {'minimum_should_match': 65, 'tie_breaker': 0.8157351798883087, 'url|boost': 0.11193686639003443, 'title|boost': 1.9153648992091248, 'body|boost': 4.1235310194877615}\n",
      "Final params: {'operator': 'OR', 'minimum_should_match': 65, 'tie_breaker': 0.8157351798883087, 'url|boost': 0.11193686639003443, 'title|boost': 1.9153648992091248, 'body|boost': 4.1235310194877615}\n",
      "\n",
      "CPU times: user 38.6 s, sys: 12.7 s, total: 51.3 s\n",
      "Wall time: 35min 13s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "_, _, final_params_boosts, metadata_boosts = optimize_query_mrr100(es, max_concurrent_searches, index, template_id,\n",
    "    config_space=Config.parse({\n",
    "        'method': 'random',\n",
    "        'num_iterations': 75,\n",
    "        'space': {\n",
    "            'minimum_should_match': { 'low': 30, 'high': 70 },\n",
    "            'tie_breaker': { 'low': 0.0, 'high': 1.0 },\n",
    "            'url|boost': { 'low': 0.0, 'high': 10.0 },\n",
    "            'title|boost': { 'low': 0.0, 'high': 10.0 },\n",
    "            'body|boost': { 'low': 0.0, 'high': 10.0 },\n",
    "        },\n",
    "        'default': {\n",
    "            'operator': 'OR',\n",
    "        }\n",
    "    }),\n",
    "    verbose=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 25 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = plot_objective(metadata_boosts, sample_source='result')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Evaluation with: MRR@100\n",
      "Score: 0.2966\n",
      "CPU times: user 1.91 s, sys: 587 ms, total: 2.5 s\n",
      "Wall time: 1min 27s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "_ = evaluate_mrr100_dev(es, max_concurrent_searches, index, template_id, params=final_params_boosts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So with the same number of iterations, we're not able to do any better than Bayesian optimization by just doing a random search. This is probably intuitive, but random search can sometimes be a good approach. Typically it does require more iterations than Bayesian optimization though. This is consistent with [previous findings](https://papers.nips.cc/paper/2011/file/86e8f7ab32cfd12577bc2619bc635690-Paper.pdf) that show that manual tuning and random search are typically not as good at finding optimal hyperparameter than automatic sequential optimization like Bayesian optimization."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion\n",
    "\n",
    "In this notebook we covered grid searches for discrete parameter spaces and Bayesian optimization for large and continuous parameter spaces. We tried some experiments with very large parameter spaces as well. In the end, the methods did not differ that much in the final MRR@100 score on the development dataset. What we can conclude though is that there are sometimes relationships between parameters of a query and those need to be dealt with either by tuning stepwise, or trying to tune all at once. Furthermore, it can make sense to use step-wise optimization to get a better understanding of the meaning of parameters, the relationships between parameters, and often the performance tradeoffs. The latter is something we haven't gone into here, but for production workloads, it's important to understand not just the relevance metrics but the performance metrics as well. There are certainly times when you want to trade-off relevance for performance. It's also important to note that there are limitations to the size of the parameter space that Bayesian optimization will work well for. This is another reason to work step-wise and hold some parameters constant while tuning a new set of parameters either with a grid search or Bayesian optimization.\n",
    "\n",
    "We hope that this notebook provides you with some ideas, some learnings, and a good foundation on which to tune your own search queries!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
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    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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